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Record W3082158481 · doi:10.1002/mds.28238

Age at Onset of <scp>LRRK2</scp> p.<scp>Gly2019Ser</scp> Is Related to Environmental and Lifestyle Factors

2020· article· en· W3082158481 on OpenAlexfundno aff
Theresa Lüth, Inke R. König, Anne Grünewald, Meike Kasten, Christine Klein, F. Hentati, Matthew J. Farrer, Joanne Trinh

Bibliographic record

VenueMovement Disorders · 2020
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsLRRK2Interquartile rangeMedicineInternal medicinePopulationParkinson's diseaseGerontologyEnvironmental healthDisease

Abstract

fetched live from OpenAlex

ABSTRACT Objectives The effect of environmental and lifestyle factors on patients with LRRK2 (leucine‐rich repeat kinase 2) p.Gly2019Ser (LRRK2 + /PD + ) compared to idiopathic PD (iPD) has yet to be thoroughly investigated. Methods In a homogeneous Tunisian Arab Berber population, we recruited 200 idiopathic PD and 199 LRRK2 p.Gly2019Ser mutation carriers, of whom 142 had PD (LRRK2 + /PD + ) and 57 were unaffected (LRRK2 + /PD − ). Case report form (CRF) questionnaires (motor and non‐motor symptoms) including the Geoparkinson Questionnaire were used to assess environmental and lifestyle factors. Results In LRRK2 + /PD + , tobacco use was significantly associated with a later median age at onset (AAO). The median AAO was 60 years (interquartile range = 52–67.25) for tobacco users, compared to 52 years (interquartile range = 45.25–61) for non‐users ( P = 0.0042 at adjusted α = 0.025). Additionally, we observed an independent but additive effect of black tea consumption and tobacco use. Conclusions Our data suggest that tobacco and black tea have a protective effect on age at onset in LRRK2 + /PD + . © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.225
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations51
Published2020
Admission routes1
Has abstractyes

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